“You’re Gay, It’s Just What Happens”: Sexual Minority Men Recounting Experiences of Unwanted Sex in the Era of MeToo
Bibliographic record
Abstract
Our grounded theory analysis derives from in-depth interviews conducted with 24 gay, bisexual, queer, and other men who have sex with men (GBM) living in Toronto, Canada, to understand their experiences of sexual coercion. Participants drew on discourse from the #MeToo movement to reconsider the ethics of past sexual experiences. The idea that gay or queer sex is inherently risky and unique from heterosexual relations made negotiating sexual safety challenging. These notions were enforced by homophobic discourses on the one hand, and counter discourses of sexual liberation, resistance to heteronormativity, hegemonic masculinity, and HIV prevention on the other. Biomedical advances in HIV prevention such as pre-exposure prophylaxis (PrEP) and undetectable viral load affected how some participants felt about sexual autonomy and safety. Participants held themselves responsible for needing to be more assertive within sexual encounters to avoid coercion. Many believed that unwanted sex is unavoidable among GBM: if "you're gay, it's just what happens." Targeted education aimed at GBM communities that incorporates insights on GBM sexual subcultures is necessary. This work must be situated within a broader understanding of how gender norms and hegemonic masculinity, racism, HIV status, and other power imbalances affect sexual decision-making, consent, pleasure, and sexual harm.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.021 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".